[ICML-2026] Official implementation of "SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience"
-
Updated
Aug 7, 2025 - Python
[ICML-2026] Official implementation of "SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience"
Scalable pipeline for synthesizing verifiable RLVR training data for computer-use agents
PreAct: Computer-Using Agents that Get Faster on Repeated Tasks (arXiv:2606.17929). Compile successful runs into verified state-machine programs and replay them 8.5–13× faster with no per-step LLM calls.
Environment-Native Verified Search (ENVS): GUI agent post training pipeline that reaches higher accuracy at lower compute than online RL.
GUI trajectory annotation: QEMU desktop VM + input-event tracing + screenshot pairing, with a web console for review & export.
Evaluation of GPT-4o-mini on OSWorld desktop automation benchmark. Compares screenshot-only vs accessibility tree-enhanced approaches across 10 tasks (Chrome, LibreOffice, file ops, etc). Documents critical coordinate extraction failures and provides architectural recommendations for GUI agents.
Edge-optimized OpenCUA-7B computer-use agent evaluated on OSWorld, exploring systematic vLLM inference optimizations across CPU and GPU, including precision tuning, image history management, speculative decoding, and prefix caching.
Text-only semantic computer-use runtime for a modified OSWorld Linux environment
Training-free hover evidence and visual attention guidance for GUI agents
Provider-neutral enhanced Qwen2.5-VL agent and evaluation runner for OSWorld
SCoR: a sparse subtask planner over a frozen GUI executor (EMNLP 2026)
To associate your repository with the osworld topic, visit your repo's landing page and select "manage topics."